IBM Ventures works as the intermediary between startups and Big Blue, the technology giant whose staff of 380,000 serves clients in 170 countries. The Ventures unit links startups with relevant IBM teams and seeks co-working possibilities in marketing and sales channels, in addition to making classical VC investments. We talked with Christoph Auer-Welsbach, partner at IBM Ventures, at the TechChill conference in Riga.

What is the nature of your venture capital business?

We do not have a fund at the moment. We have the Watson fund where we have made five investments in the past. Those were business unit investments or investments from the balance sheet. We make business unit investments from the IoT side, and from the data and analytic side. We also make acquisitions of later-stage companies, usually on private equity. That’s done by our M&A department.

How are you different from other corporate VCs?

The difference is in the strong enterprise market that we serve, as well as our efforts to participate in digitalisation, the SaaS economy with APIs, cloud platforms and their connected services, and our success in this area.

If you look at other VCs, they start from the consumer side and try to move to the enterprise side. We are on the enterprise side and try to stay there. It is an interesting value-add. In the US, mainly in the Bay Area, there is more focus on deep tech support and industry knowledge.

Outside the US it is different – we usually focus on helping growth companies with scaling, building up sales machines, building their brands within their vertical, trying to improve and grow their processes and operations, and to grow internationally.

IBM was a company that made a big comeback at a corporate level in the 1980s. Is it in a similar position now?

Based on my feelings, yes. I can only compare it to what I have heard – I was born in the 1980s. Back then there was a shift into technology consulting. Now we are focusing on the digital economy, trying to digitise our products and solutions to make them available in the cloud through SaaS business models, and constantly improving: providing product support, implementing the forward-deployed engineering model.

We are definitely on the move – even more so in Watson. We moved from hardware to software, and now from software into intelligence and intelligence software.

For the startup community, I think Watson is the only thing they know about IBM.

IBM is a massive company and there are cultural differences. I joined IBM in January 2016 and joined the Watson team to lead the strategic partnerships in the European region. The team is interesting: on average it has younger people – closer to the new types of client. That is the new emerging culture. I don’t like black and white discussions, I like a mix of old and new. To have the old, established knowledge about how to make business, combined with the new approach of testing and trying it out, freemium, and finding the balance within that.

From an outside perspective, how much do you think you can use Watson as a vehicle to raise interest within the startup community?

Watson started out as a research project – as the Grand Challenge in the 2000s. In terms of how to utilise the specific technologies in the cognitive artificial intelligence (AI) arena, I would say that IBM is at the forefront.

People do not really understand the difference between cognitive and real AI. Some tools are intelligent or pretend to be intelligent, some tools are capable of carrying out pattern magic, extending our cognitive capabilities. When thinking about the product, it is not particular to Watson – it is in everything we do at IBM. All our cloud products, solutions and APIs will be infused by Watson in the long term. If you look at the Watson IT-platform itself, it uses core technologies from Watson, because that is necessary when you connect all the sensors. You need some sort of intelligence and automation of the backend processes – how else can you make sense out of thousands of sensors. So Watson is, and will be, the core of everything that we do.

I am sure IBM is not the only company trying to do this, but it is our fresh, young brand.

This is a big differentiator at a time when every other startup wants to be an AI startup.

This is an issue. It’s like big data. 8-10 years ago every startup was a big data startup. Now it’s an AI startup.

They are the same startup.

Exactly. That is a big difference with Watson – we have some real consumer-use cases that are pretty successful, in healthcare for example. It is a balance that IBM can take in terms of size.

We can also give back, making things available to everybody else so that they can try them and perhaps make some business with them.

From the IBM Ventures and Watson perspective, is healthcare one of the key verticals?

The venture arm aligns with all our strategic imperatives – it is on the AI-cognitive, fintech-blockchain and cloud infrastructure sides, all combined with data analytics and healthcare. IoT is something that is everywhere – it is not its own vertical.

The healthcare perspective is important in terms of what we do product-wise and from the venture side.

When you look at it from an industry perspective, finance, retail and healthcare are the most impactful industries globally in terms of our lives. From the venture perspective, it is interesting to see where the market is going. For example, we work with large renowned cancer research centres that have extended knowledge insights with goals stretching to 25+ years for their studies.

When working with the market we are looking at the immediate needs and how can we solve them. So we look more at those areas in the venture arm – what can we do in the next five years, what can be done right away with the technology available today, how can we improve tomorrow’s technology to make it happen.

When you look at the healthtech sector for startups, do you look for investment cases or corporate partners?

Both. It is important to me that the startup uses cutting-edge technologies for analytics, computer vision and natural language processing. For example, within Watson we have made efforts to analyse our natural spoken language to analyse the status of your mental health. We also run a project where we focus on measuring body movements and how this relates to general health. This pattern-matching has a huge impact. From a device perspective, we don’t really focus on high-end devices – we focus on how you can make use of the least amount of data to draw conclusions for general health issues. For example, I just met a company in Stockholm that scans you to measure body mass index. With the same index

This pattern-matching has a huge impact. From a device perspective, we don’t really focus on high-end devices – we focus on how you can make use of the least amount of data to draw conclusions for general health issues. For example, I just met a company in Stockholm that scans you to measure body mass index. With the same index

For example, I just met a company in Stockholm that scans you to measure body mass index. With the same index number you could be ok, but I may not be – we look the same from the outside but may be different inside. That is an interesting technology. For them it takes a couple of minutes or a few hours – before it took weeks and the costs were much higher. These are innovations, where machine-vision technology is being used in a novel way that has a real impact.

Process inefficiencies – an increase in speed or lowered friction in how to measure something – are areas that are very relevant right now, because they are highly-applicable in the market. Not only from a business model perspective but also from a testing and validation perspective. If we can measure everybody’s body mass index that accurately and quickly on a frequent basis, we can carry out a study in the next two years. Does it really have an impact, is it relevant, does it help us to change behaviours to live healthier lives?

With healthcare do you need to have relatively long perspective?

I think that is what most people get wrong in the startup environment. When I look at a company I want to see founders who want to build a 100-year company. I don’t want to see a founder who wants to build an app. It needs to be for the long term. In healthcare it is mostly related to the research, because gathering results takes a long time. Founders or startups need to have a clear view of the different time frames in which they can perform for specific activities and tasks.

If I launch something on the web, I can do it overnight, possibly have a client the next day and never need an investor. In healthtech I need to spend two years researching something and I need money for that. Capital is needed before you can prove anything.

In healthcare investors know that the timelines are different to consumer tech companies, just to exchange experience and expertise. They can get another, qualified opinion on their vision: is the vision they set out with achievable, is it feasible, manageable in the proposed timeframe?

They can ask if we have experience of specific milestones that they can set along the way – are those realistic – and are there similar activities globally that they could look at as a proof of concept to convince investors? If you look at the healthcare space you often have very young founders who come straight out of universities, trying to bootstrap for as long as they can. They usually enter the B2C healthcare space: patient care, doctors, apps etc.

If you look at areas of the healthcare sector where there is more deep technology, they are usually PhDs who have already worked for a couple of years internally and at some point have started the company when they think they have an opportunity to commercialise. Or they are second or third time entrepreneurs. They have done similar things in the past so the risk is reduced and operational risk is based on pure visibility. It’s trial and error.

It is very similar for IBM from the venture perspective too. We are looking for B2B and enterprise. Enterprise always has longer sales cycles – it has a different approach. But the gains you can get can be more rewarding, because customers are usually more loyal.

It seems to me to me that for much of the money out there, they do not take an approach of investing in startups that are built for 100 years.

IBM is now 106 years old. We can refer to that and say we have been successful with it. In today’s open, sharing economy, where everything is an open standard and we could potentially switch between services, you start trusting the company and services – you rely on it and the people. It is important to think about the long term in the enterprise game.

I would say that most VCs have the ability to think in the long term in relation to building a company. When you ask a VC, they usually say they want founders and entrepreneurs with a strong vision and plan. So, I would say, deep inside they do think about that. But they are stuck in their financial model of investing for five years, then having another five years to get the cash out. A typical fund term is 10 years, so they are stuck in this model.

In IBM Ventures we have a different approach. We have the advantage of saying we have a strong business in the bag and we invest from the profits we generate. We can leverage our other resources from a market and technology perspective. So maybe it is also easier for IBM Ventures to have this kind of strong focus.

If you invest in a startup, they start to work with you and they use your retail channel. Do they often see a risk of big bad blue?

I think a lot of startups these days do not have relevant experience in the enterprise base or the right perception of it. They go out to tech conferences, which usually support that kind of feeling. They may meet a VP of Watson and he is interested in them, so they think, “wow, this is my next 150,000 deal.” But that is not the case. It is the great connection, maybe a mentoring connection or a great opportunity to associate themselves and gain expert knowledge. It is not a sales opportunity. You need to be in the right stage of the startup to handle this kind of relationship. If a company comes to IBM, is introduced to a specific business unit and agrees to a partnership on sales and distribution, they suddenly have to deal with 10 meetings every week with large companies and corporations. But they may only have 10 people – how do they support that? We are looking for growth stage companies and late stage companies – late A, Series B+ – because we know they have sales skills. We know they have marketing and know how to deal with smaller clients. They know that processes take longer and have the resources to invest in it. Internally, we focus on making sure we also have the right people and teams to introduce to them. You can have the smartest people and brightest minds on the sales and tech side in IBM and not be compatible because they don’t have the experience. It is not a bad thing, it is simply that they have a different focus. On the other hand, we have people who know about partnerships and have dealt with

We are looking for growth stage companies and late stage companies – late A, Series B+ – because we know they have sales skills. We know they have marketing and know how to deal with smaller clients. They know that processes take longer and have the resources to invest in it. Internally, we focus on making sure we also have the right people and teams to introduce to them. You can have the smartest people and brightest minds on the sales and tech side in IBM and not be compatible because they don’t have the experience. It is not a bad thing, it is simply that they have a different focus. On the other hand, we have people who know about partnerships and have dealt with

Internally, we focus on making sure we also have the right people and teams to introduce to them. You can have the smartest people and brightest minds on the sales and tech side in IBM and not be compatible because they don’t have the experience. It is not a bad thing, it is simply that they have a different focus. On the other hand, we have people who know about partnerships and have dealt with

You can have the smartest people and brightest minds on the sales and tech side in IBM and not be compatible because they don’t have the experience. It is not a bad thing, it is simply that they have a different focus. On the other hand, we have people who know about partnerships and have dealt with startups before. Our goal is to make sure that we are the right intermediary and everybody sees success at the end of the day, otherwise, it is a waste of time, which is bad for both sides. It’s about understanding the value of the partnership, understanding the stage of the partnership and yourself. Where are you at this point in time? If you have 6 people you cannot usually survive a partnership with IBM or a similar-sized corporation.

It’s about understanding the value of the partnership, understanding the stage of the partnership and yourself. Where are you at this point in time? If you have 6 people you cannot usually survive a partnership with IBM or a similar-sized corporation.

In the previous CoFounder issue, Samsung also mentioned problems that might arise from a startup’s cooperation with a very big company. It must be challenging when Samsung or IBM is on the other side of the table.

Yes, it is. Based on my experience with early stage companies I would also argue that sales is a general issue in the startup community. It is less of an issue in the US than in Europe. Startups often do not know how to sell and do not focus on it. They focus on product and tech. That is great, but sales are one of the biggest components. If you cannot sell, the best product can be worthless.

We are about to launch a distillery and are talking about the same topic.

It’s the perception. We buy with our eyes. It can look great or it can be terrible. There are IoT and AI products out there that have a cool brand but don’t actually work properly.

There is the same challenge with the wearables boom – I have five of them but do not use any of them.

There are a couple of components there that can make it a success or not. One is a culture issue. I like to wear a watch, but a watch is still a watch. I use it more from a lifestyle perspective. Like women like wearing bracelets. I would turn off all the notifications on my phone if I got them on my watch – it would be too distracting. But these are cultural differences – younger people may like it and might find it attractive.

I think the real value will come later when we can really distill the information that helps us improve our habits. That’s what wearables are supposed to do, but just measuring my movements or how many steps I take does not help me.

From the IBM and IBM Ventures perspective, what are you really looking for with startups and new technologies?

We are looking for technologies that can launch the next wave of technology like we had with the Internet. Now we are in the next phase – is it blockchain? Decentralisation of everything? Do we want to fly to Mars or do we want to have robots doing all the work for us? Battery could be one technology. Energy – Elon Musk – that is one of the next frontiers. It is great to have a phone, but how can we change our energy consumption with all the technology we have? That is the most frequently asked question I have for all kinds of devices. If we have a tracking device that is smart, thin, unobtrusive and just works, I can imagine it might be implemented in your glasses or belt. You don’t need to worry about it. When it’s not intrusive, when it’s just there, then it becomes interesting. It becomes a foundational technology layer, like automated watches. They run automatically all the time – nobody thinks about it.

Launching something that needs a human behaviour to change for adoption is just crazy.

That is where AI hopefully comes in. Its intelligence products – products that adjust and adapt to our lives. Right now, your grandma or babysitter needs to understand how the TV works. Everybody has two remote controls. AI is set to change this, so that everybody can just use it. It adapts to my behaviour and language. That’s the real game-changer. It is about having more than one way of communicating. Intelligence will be through movement, visuals, tonality, voice and the combination of these – not just one medium.